소셜미디어 콘텐츠 주제와 고객 인게이지먼트 간의 관계분석: 머신러닝 방법론을 중심으로An Analysis on the Relationship Between Content Topics of Social Media and Customer Engagement Using Machine Learning Methodology
- Other Titles
- An Analysis on the Relationship Between Content Topics of Social Media and Customer Engagement Using Machine Learning Methodology
- Authors
- 이중원; 박철
- Issue Date
- 2021
- Publisher
- 한국경영학회
- Keywords
- Social media; Customer engagement; Contents marketing; Machine learning; Topic modeling; Zero-inflated negative binomial regression
- Citation
- 경영학연구, v.50, no.1, pp.115 - 142
- Indexed
- KCI
- Journal Title
- 경영학연구
- Volume
- 50
- Number
- 1
- Start Page
- 115
- End Page
- 142
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/50675
- DOI
- 10.17287/kmr.2021.50.1.115
- ISSN
- 1226-1874
- Abstract
- Customer engagement is regarded as a performance indicator of social media marketing, and previous studies have reported that the characteristics of content to increase customer engagement. However, the topic of content has not been sufficiently studied. This study analyzes the relationship between the topic of social media content and customer engagement and suggests an analysis procedure that can apply a machine learning model, a key tool for recent digital transformation. For empirical analysis, 154,705 social media data of 51 global brands were collected, and content topics were classified using a topic modeling method. And the relationship between content topic and customer engagement was analyzed using zero-inflated negative binomial regression analysis and machine learning model. As a result of the analysis, contents of 51 brands were classified into 18 contents topics, and there was a difference in the impact on customer engagement according to the topic. In addition, using a machine learning model, it was possible to predict the customer engagement performance of the content with an accuracy of about 90%. This study contributed to the marketing literature by analyzing the relationship between social media content topics and customer engagement through machine learning methodology.
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Collections - College of Global Business > Global Business in Division of Convergence Business > 1. Journal Articles
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